Results 251 to 260 of about 37,022,242 (283)
Some of the next articles are maybe not open access.
Content-based image retrieval methods
Programming and Computer Software, 2009Creation of a content-based image retrieval system implies solving a number of difficult problems, including analysis of low-level image features and construction of feature vectors, multidimensional indexing, design of user interface, and data visualization.
openaire +2 more sources
Prefetching for content-based image retrieval
Proceedings. IEEE International Conference on Multimedia and Expo, 2003Currently, research on content-based image retrieval (CBIR) is focused on the improvement of retrieval performance using relevance feedback techniques. However, for the remote user, retrieval latency is also a critical metric of satisfaction. In this paper, we show how to integrate the prefetching mechanism into the CBIR system in order to reduce ...
Janghyun Yoon, Nikil Jayant
openaire +2 more sources
Content based image retrieval with LIRe
Proceedings of the 19th ACM international conference on Multimedia, 2011LIRe (Lucene Image Retrieval) is an open source library for content based image retrieval. Besides providing multiple common and state of the art retrieval mechanisms it allows for easy use on multiple platforms. LIRe is actively used for research, teaching and commercial applications.
openaire +1 more source
Private Content Based Image Retrieval
2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008For content level access, very often database needs the query as a sample image. However, the image may contain private information and hence the user does not wish to reveal the image to the database. Private content based image retrieval (PCBIR) deals with retrieving similar images from an image database without revealing the content of the query ...
Jagarlamudi Shashank +3 more
openaire +1 more source
Content Based Image Retrieval for Unsegmented Images
2003We present a new method for image retrieval by shape similarity able to deal with real images with not uniform background and possible touching/occluding objects. First of all we perform a sketch-driven segmentation of the scene by means of a Deformation Tolerant version of the Generalized Hough Transform (DTGHT). Using the DTGHT we select in the image
M. ANELLI, A. MICARELLI, SANGINETO E
openaire +4 more sources
Content-Based Image Retrieval for Medical Image
2015 11th International Conference on Computational Intelligence and Security (CIS), 2015In this paper, the SIMPLIcity (Semantics-sensitive Integrate Matching for Picture Libraries), an image retrieval system is introduced. The feature extraction is based on Histogram, color layout and coefficients of wavelet transform. This retrieving system adopts feature database for matching so as to reduce the search space which is especially useful ...
openaire +2 more sources
2008 6th International Symposium on Intelligent Systems and Informatics, 2008
A picture is worth a thousand words. Yes, but which ones? Content-based image retrieval (CBIR) is the application of computer vision to the image retrieval problem. The image retrieval problem is the problem of searching for digital images in large databases.
Igor Marinovic, Igor Furstner
openaire +1 more source
A picture is worth a thousand words. Yes, but which ones? Content-based image retrieval (CBIR) is the application of computer vision to the image retrieval problem. The image retrieval problem is the problem of searching for digital images in large databases.
Igor Marinovic, Igor Furstner
openaire +1 more source
2009
Content-Based Image Retrieval (CBIR) aims to search images that are perceptually similar to the querybased on visual content of the images without the help of annotations. The current CBIR systems use global features (e.g., color, texture, and shape) as image descriptors, or usefeatures extracted from segmented regions (called region-based descriptors).
Ming Zhang, Reda Alhajj
openaire +3 more sources
Content-Based Image Retrieval (CBIR) aims to search images that are perceptually similar to the querybased on visual content of the images without the help of annotations. The current CBIR systems use global features (e.g., color, texture, and shape) as image descriptors, or usefeatures extracted from segmented regions (called region-based descriptors).
Ming Zhang, Reda Alhajj
openaire +3 more sources
Advanced Content Based Image Retrieval for Fashion
2015In this paper we propose a new content based approach for clothing image retrieval trying to mimic the human vision understanding not only based on naive manipulation of texture and color, but also combining some recent and advanced techniques like human pose estimation, super-pixel segmentation and cloth parsing.
Dagnew, Tewodros Mulugeta +1 more
openaire +3 more sources